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Who understands Low German today and who can speak it? Who makes use of media and cultural events in Low German? What images do people in northern Germany associate with Low German and what is their view of their regional language?
These and further questions are answered in this brochure with the help of representative data collected in a telephone survey of a total of 1,632 people from eight federal states (Bremen, Hamburg, Lower Saxony, Mecklenburg-West Pomerania and Schleswig-Holstein as well as Brandenburg, North Rhine-Westphalia and Saxony-Anhalt).
This White Paper sets out commonly agreed definitions on activities of consortia within NFDI. It aims to provide a common basis for reporting and reference regarding selected questions of cross-consortial relevance in DFG’s template for the Interim Reports. The questions were prioritised by an NFDI Task Force on Evaluation and Reporting (formerly Task Force Monitoring) as a result of discussing possible answers to the DFG template. In this process the need to agree on a generalizable meaning of terms commonly used in the context of NFDI, and reporting in particular, were identified from cross-consortial perspectives. Questions that showed the highest requirement on clarification are discussed in this White Paper. As NFDI evolves, the Task Force will likely propose further joint approaches for reporting in information infrastructures.
While each of broad relevance, the questions addressed relate to substantially different aspects of consortia’s work. They are thus also structured slightly different.
Collaborative work in NFDI
(2023)
The non-profit association National Research Data Infrastructure (NFDI) promotes science and research through a National Research Data Infrastructure. Its aim is to develop and establish an overarching research data management (RDM) for Germany and to increase the efficiency of the entire German science system. After a two-and-a-half year build up phase, the process of adding new consortia, each representing a different data domain, has ended in March 2023. NFDI now has 26 disciplinary consortia (and one additional basic service collaboration). Now the full extent of cross-consortial interaction is beginning to show.
New KARL (Knowledge Acquisition and Representation Language) allows to specify all parts of a problem-solving method (PSM). It is a formal language with a well-defined semantics and thus allows to represent PSMs precisely and unambiguously yet abstracting from implementation detail. In this paper it is shown how the language KARL has been modified and extended to New KARL to better meet the needs for the representation of PSMs. Based on a conceptual structure of PSMs new language primitives are introduced for KARL to specify such a conceptual structure and to support the configuration of methods. An important goal for this extension was to preserve three important properties of KARL: to be (i) a conceptual, (ii) a formal, and (iii) an executable language.
This technology watch report discusses digital repository solutions, in the context of the research infrastructure projects CLARIAH-DE, CLARIN, and DARIAH. It provides an overview of different repository systems, comparing them and discussing their respective applicabilities from the perspectives of the project partners at the time of writing.
KoralQuery 0.3
(2015)
KoralQuery is a general corpus query protocol (i.e. independent of research tasks and corpus formats), serialized in JSON-LD [1]. KoralQuery focuses on simplicity of implementation rather than human readibility and writability. Support for a growing number of query languages is granted by the Koral serialization processor.
CLARIAH-DE cross-service search - prospects and benefits of merging subject-specific services
(2021)
CLARIAH-DE combines services and offerings of CLARIN-D and DARIAH-DE. This includes various search applications which are made directly available to researchers. These search applications are presented in this working paper based on their main characteristics and compared with a focus on possible harmonizations. Opportunities and risks of different forms of technical integration are highlighted. Identified challenges can be explained in particular considering the background of different organizational and technical frameworks as well as highly specific and discipline-dependent requirements. The integration work that has already been carried out and the experiences gained with regard to future work and possible integration of further applications are also discussed. The experiences made in CLARIAH-DE can especially be of interest for other projects in the field of digital research infrastructures.
A topic in the field of knowledge acquisition is the reuse of components that are described at the knowledge level. Problems concern the description, indexing and retrieval of components. In our case there is the additional feature of integrating so called automated building blocks in a knowledge level description. This paper describes what knowledge level descriptions of components for reuse should look like, and proposes a way to describe assumptions and requirements that are to be made explicit. In the paper an extension of the “normal” knowledge acquisition setting is made in the direction of machine learning components.